Salesforce Einstein Language predicts customer intent and sentiment from text to personalize outreach. The four-step workflow trains custom models on your data, tests them with built-in metrics, then uses predictions to improve communications.
In this video, we'll explore how you can use Salesforce Einstein to predict the intent and sentiment of text so you can communicate more effectively with employees and customers. Einstein Language draws meaning from all kinds of text inputs like customer service inquiries, forms and notes to give you valuable customer insight.
Here's how it works. The first step is to gather and categorize sample data. For example, a social comment like this product is a game changer. My curly hair has never looked so great. Could be recognized as an upsell opportunity for other products in the product line. Next, Einstein creates models just for you. This can take a few minutes or hours depending on the size of your data set. Now you can test your model to make sure the predictions are correct. Einstein provides all the model metrics you could possibly need. Finally, use your predictions. Here you see how Einstein Language helped the marketer know the perfect content to send to their customer based on the type of content they were interested in.
With Einstein Language, you can build smart apps that leverage the power of deep learning to engage your customers like never before. See what else Einstein can do for you. Discover hidden insights, predict future outcomes, recommend the best action, and automate processes with Salesforce Einstein. Explore einstein language at trailhead.
